Alexander Staab

54 papers receiving 2.1k citations

Alexander Staab's Hit Papers

Good Practices in Model‐Informed Drug Discovery and Development: Practice, Application, and Documentation 2015 · 276 citations
2760+3+7Years since publication50100150200250

Peers

Alexander Staab
Comparison fields: 5 of 120
  • Internal Medicine 136
  • Pharmacology 164
  • Oncology 467
  • Statistics and Probability 159
  • Cardiology and Cardiovascular Medicine 352
Replace Vijay Upreti with:
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Rajanikanth Madabushi United States
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Paolo Carraro Italy
Maureen Kavanah United States
Jeffry Florian United States
Benoı̂t Blanchet France
Guy Montay France
Teddy Kosoglou United States
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Citations per year

Countries citing papers authored by Alexander Staab

Since Specialization
Citations

This map shows the geographic impact of Alexander Staab's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Alexander Staab with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Alexander Staab more than expected).

Fields of papers citing papers by Alexander Staab

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Alexander Staab. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Alexander Staab. The network helps show where Alexander Staab may publish in the future.

Co-authors

The 25 scholars most cited alongside Alexander Staab, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Alexander Staab Line = papers co-authored together Alexander Staab links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 54 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Good Practices in Model‐Informed Drug Discovery and Development: Practice, Application, and Documentation
Hit paper breakdown →
2015276
2 2006255
3 2011246
4 2014113
5 201892
6 201985
7 200782
8 201179
9 201569
10 200754
11 200149
12 201046
13 200944
14 201043
15 201442
16 201341
17 200640
18 201534
19 200931
20 201330

About Alexander Staab

Alexander Staab is a scholar working on Endocrinology, Diabetes and Metabolism, Oncology, Cardiology and Cardiovascular Medicine, Pulmonary and Respiratory Medicine and Molecular Biology, having authored 54 papers that have together received 2.1k indexed citations. Recurring topics across this work include Diabetes Treatment and Management (9 papers), Health Systems, Economic Evaluations, Quality of Life (4 papers), Peptidase Inhibition and Analysis (4 papers), Atrial Fibrillation Management and Outcomes (4 papers), Statistical Methods in Clinical Trials (4 papers), Pharmaceutical studies and practices (3 papers), Lung Cancer Treatments and Mutations (3 papers) and Neuropeptides and Animal Physiology (3 papers). The work is most often cited by research in Internal Medicine (136 citations), Pharmacology (164 citations), Oncology (467 citations), Statistics and Probability (159 citations) and Cardiology and Cardiovascular Medicine (352 citations). Alexander Staab has collaborated with scholars based in Germany, United States and Spain. Frequent co-authors include Thorsten Lehr, Charlotte Kloft, Karl‐Heinz Liesenfeld, Sebastian Haertter, Paul Reilly, Guus A.M.S. van Dongen, Bernard M. Tijink, Jan Buter, Giuseppe Giaccone and C. René Leemans. Their work appears in journals such as British Journal of Clinical Pharmacology, CPT Pharmacometrics & Systems Pharmacology, Clinical Pharmacokinetics, Pharmaceutical Research and The Journal of Clinical Pharmacology.

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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